Cargando…
A Feasibility Study of Deep Learning-Based Auto-Segmentation Directly Used in VMAT Planning Design and Optimization for Cervical Cancer
PURPOSE: To investigate the dosimetric impact on target volumes and organs at risk (OARs) when unmodified auto-segmented OAR contours are directly used in the design of treatment plans. MATERIALS AND METHODS: A total of 127 patients with cervical cancer were collected for retrospective analysis, inc...
Autores principales: | Chen, Along, Chen, Fei, Li, Xiaofang, Zhang, Yazhi, Chen, Li, Chen, Lixin, Zhu, Jinhan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9198405/ https://www.ncbi.nlm.nih.gov/pubmed/35719942 http://dx.doi.org/10.3389/fonc.2022.908903 |
Ejemplares similares
-
Evaluation of auto‐planning in IMRT and VMAT for head and neck cancer
por: Ouyang, Zi, et al.
Publicado: (2019) -
Evaluation of auto-planning in VMAT for locally advanced nasopharyngeal carcinoma
por: Jihong, Chen, et al.
Publicado: (2022) -
Plan quality and treatment efficiency assurance of two VMAT optimization for cervical cancer radiotherapy
por: Huang, Sijuan, et al.
Publicado: (2023) -
Dosimetry study of Auto-VMAT planning and Manual-VMAT planning based on Pinnacle(3) 9.10 in radiotherapy for cervical cancer
por: Sun, Haitao, et al.
Publicado: (2023) -
A study of minimum segment width parameter on VMAT plan quality, delivery accuracy, and efficiency for cervical cancer using Monaco TPS
por: Wang, Yuanyuan, et al.
Publicado: (2018)